5 papers
Rényi Tracking Bounds for Langevin Dynamics with Moving Targets
Yuchen Xin, Jingxin Zhan, Zhihua Zhang
We study Langevin diffusion and Langevin Monte Carlo (LMC) when the target distribution changes over time. Under a log-Sobolev inequality (LSI), we derive non-asymptotic Rényi-dive…
Does 1/2-Tsallis-INF Also Work Well for Best-Arm Identification?
Jingxin Zhan, Yuze Han, Zhihua Zhang
Regret minimization (RM) and best-arm identification (BAI) are two fundamental objectives in multi-armed bandits. Among regret-minimizing algorithms, -Tsallis-INF is a canonic…
Last-Iterate Analyses of FTRL with the 1/2-Tsallis Entropy in Stochastic Bandits
Jingxin Zhan, Yuze Han, Zhihua Zhang
The convergence analysis of online learning algorithms is central to machine learning theory, where the last-iterate convergence is particularly important, as it captures the learn…
Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems
Jingxin Zhan, Yuchen Xin, Chenjie Sun +1
We consider a common case of the combinatorial semi-bandit problem, the -set semi-bandit, where the learner exactly selects arms from the total arms. In the adversarial…
A Regularized Online Newton Method for Stochastic Convex Bandits with Linear Vanishing Noise
Jingxin Zhan, Yuchen Xin, Kaicheng Jin +1
We study a stochastic convex bandit problem where the subgaussian noise parameter is assumed to decrease linearly as the learner selects actions closer and closer to the minimizer…